REMAKE
REcovery of Motor functions After stroKE: exploiting and enhancing residual abilities of the upper body beyond compensatory strategies
| Coordinatore | UNIVERSITA DEGLI STUDI DI GENOVA
Organization address
address: VIA BALBI 5 contact info |
| Nazionalità Coordinatore | Italy [IT] |
| Totale costo | 100˙000 € |
| EC contributo | 100˙000 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2012-CIG |
| Funding Scheme | MC-CIG |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-07-01 - 2017-06-30 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
UNIVERSITA DEGLI STUDI DI GENOVA
Organization address
address: VIA BALBI 5 contact info |
IT (GENOVA) | coordinator | 100˙000.00 |
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Obiettivo del progetto (Objective)
'The project aims at developing adaptive/smart tools, based on Body-Machine Interfaces (BMI) and robotic technologies, which may help stroke survivors to recover functions of the upper body by exploiting/enhancing their residual capabilities, while avoiding the “easy shortcut” of being content with stereotypical compensatory strategies. Stroke survivors face the dual problem of regaining independence in everyday tasks and recovering motor abilities. BMI’s address the former problem and compliant robots the latter. Our rationale is to integrate them (a real novelty in the field) with the ultimate goal of breaking stereotypical compensatory strategies in favor of a gradual and continuous functional reorganization of upper body movements, obtained by continuously adapting the interface to the subject’s status and physiological/psychological changes, such as aging, recovery, and progress of the illness. The work is organized in three general objectives: (i) TO TRANSLATE BODY-DERIVED SIGNALS onto BMI commands, encoding subjects’ state, impairment and residual abilities. (ii) TO DESIGN AND IMPLEMENT ADAPTIVE BMIs for rehabilitation devices, based on the individual characteristic of each subject. (iii) TO ENCODE INFORMATION of the subject’s state of motion and interaction with the environment INTO APPROPRIATE SENSORY FEEDBACK. If successful, the proposed research will generate the knowledge necessary for developing a new class of interfaces aimed at “learning” the subjects’ evolving abilities and adapting to their needs. These interfaces will provide their users with both assistance and rehabilitation under a unified framework. It is also expected that this approach, if successful with stroke survivors, may be extended to a larger family of devices and a broader range of pathologies.'